2020 Personal Income during COVID19 Pandemic

Consumer Sentiment as general trends.

• UMCSENT: University of Michigan Consumer Sentiment. Index 1966:Q1=100,Not Seasonally Adjusted

senti <- 
  "UMCSENT" %>% 
  tq_get(get = "economic.data", from = "2015-01-01") %>%
  rename(count = price) 

  senti %>% 
    ggplot(aes(x = date, y = count)) +
    geom_line(color = "firebrick2",size=.8) + 
    labs(
      x = "",
      y = "",
      title = "Consumer Sentiment Index per University of Michigan",
      subtitle = str_glue("Monthly from {min(senti$date)} through {max(senti$date)}")
    ) +
    theme(plot.title = element_text(color="blue", size=14, face="bold"))

Gross Domestic Income: Compensation of employees, paid: Wages and salaries (A4102C1Q027SBEA)

• Billions of Dollars,Seasonally Adjusted Annual Rate
• Quarterly
• Gross domestic income (GDI) is a measure of U.S. economic activity based on all the income earned while engaged in producing all the goods, services, and anything else that constitutes that economic activity
• GDI = Wages + Profits + Interest Income + Rental Income + Taxes - Subsidies

gdi <- 
  "A4102C1Q027SBEA" %>% 
  tq_get(get = "economic.data", from = "2019-01-01") %>%
  rename(total = price) 

  gdi %>% 
    ggplot(aes(x = date, y = total)) +
    geom_line(color = "goldenrod",size=.8) + 
    labs(
      y = "Billions of Dollars",
      x = "Quarterly", caption = "GDI = A4102C1Q027SBEA",
      title = "Gross Domestic Income: Compensation of employees, paid: Wages and salaries",
      subtitle = str_glue("Monthly from {min(gdi$date)} through {max(gdi$date)}")
    ) +
    theme(plot.title = element_text(color="blue", size=14, face="bold"))

• Personal Consumption Expenditures (NA000349Q)
• Millions of Dollars, Not Seasonally Adjusted

pce <- 
  "NA000349Q" %>% 
  tq_get(get = "economic.data", from = "2018-01-01") %>%
  rename(total = price) 

  pce %>% 
    ggplot(aes(x = date, y = total)) +
    geom_line(color = "red4",size=.8) + 
    labs(
      y = "Millions of Dollars",
      x = "Quarterly", caption = "NA000349Q",
      title = "Personal Consumption Expenditures",
      subtitle = str_glue("Quarterly from {min(pce$date)} through {max(pce$date)}")) +
    theme(plot.title = element_text(color="blue", size=14, face="bold"))

Employment during COVID19 pandemic

• All Employees, Total Nonfarm (PAYEMS)
• excluding proprietors, private household employees, unpaid volunteers, farm employees, self-employed.
• This measure accounts for approximately 80 percent of the workers who contribute to Gross Domestic Product.

labor <- 
  "PAYEMS" %>% 
  tq_get(get = "economic.data", from = "2019-01-01") %>%
   rename(count = price) 

  labor %>% 
    ggplot(aes(x = date, y = count)) +
    geom_line(color = "firebrick4",size=.8) + 
    labs(
      x = "",
      y = "",
      title = "Labor Force", caption = " ",
      subtitle = str_glue("From {min(labor$date)} through {max(labor$date)}")
    ) +
  
     theme(plot.title = element_text(color="blue", size=14, face="bold"))

Total Unemployed (U6RATE)

• Total Unemployed, Plus All Persons Marginally Attached to the Labor Force, Plus Total Employed Part Time for Economic Reasons, as a Percent of the Civilian Labor Force Plus All Persons Marginally Attached to the Labor Force (U6RATE)

u6 <- 
  "U6RATE" %>% 
  tq_get(get = "economic.data", from = "2019-01-01") %>%
   rename(count = price) 

  u6 %>% 
    ggplot(aes(x = date, y = count)) +
    geom_line(color = "orange",size=.8) + 
    labs(
      x = "",
      y = "",
      title = "Total Unemployed", caption = " ",
      subtitle = str_glue("From {min(u6$date)} through {max(u6$date)}")
    ) +
  
     theme(plot.title = element_text(color="blue", size=14, face="bold"))

• Consumer Price Index for All Urban Consumers: Meats, Poultry, Fish, and Eggs in U.S. City Average (CUSR0000SAF112)

mpfe <- 
  "CUSR0000SAF112" %>% 
  tq_get(get = "economic.data", from = "2019-01-01") 

  mpfe %>% 
    ggplot(aes(x = date, y = price)) +
    geom_line(color = "gold4",size=.8) + 
    labs(
      x = "",
      y = "", caption = "Index 1982-1984=100,Seasonally Adjusted",
      title = "CPI : Meats, Poultry, Fish, and Eggs (CUSR0000SAF112)",
      subtitle = str_glue("From {min(mpfe$date)} through {max(mpfe$date)}")
    ) +
  
     theme(plot.title = element_text(color="blue", size=14, face="bold"))

• Consumer Price Index for All Urban Consumers: All Items in U.S. City Average (CPIAUCSL)
• Consumer Price Index for All Urban Consumers: Food at Home in U.S. City Average (CUSR0000SAF11)
• Consumer Price Index for All Urban Consumers: Alcoholic Beverages at Home in U.S. City Average (CUSR0000SEFW)

cpi <- 
  "CPIAUCSL" %>% 
  tq_get(get = "economic.data", from = "2019-01-01") %>%
  rename(count = price) 

  cpi %>% 
    ggplot(aes(x = date, y = count)) +
    geom_line(color = "goldenrod4",size=.8) + 
    labs(
      x = "",
      y = "", caption = "Index 1982-1984=100,Seasonally Adjusted",
      title = "Consumer Price Index: All Items in U.S. City Average (CPIAUCSL)",
      subtitle = str_glue("Monthly from {min(cpi$date)} through {max(cpi$date)}")
    ) +
    theme(plot.title = element_text(color="blue", size=14, face="bold"))

• Consumer Price Index for All Urban Consumers: Food at Home in U.S. City Average (CUSR0000SAF11)

food <- 
  "CUSR0000SAF11" %>% 
  tq_get(get = "economic.data", from = "2019-01-01") %>%
  rename(count = price) 

  food %>% 
    ggplot(aes(x = date, y = count)) +
    geom_line(color = "goldenrod4",size=.8) + 
    labs(
      x = "",
      y = "", caption = "Index 1982-1984=100,Seasonally Adjusted",
      title = "CPI: Food at Home in U.S. City Average (CUSR0000SAF11)",
      subtitle = str_glue("Monthly from {min(food$date)} through {max(food$date)}")
    ) +
    theme(plot.title = element_text(color="blue", size=14, face="bold"))

CPI Average Price Data, U.S. city average (AP) (Select from list below) Bacon, sliced, per lb. - APU0000704111 Bananas, per lb. - APU0000711211 Bread, white, pan, per lb. - APU0000702111 Chicken, fresh, whole, per lb. - APU0000706111 Coffee, 100%, ground roast, all sizes, per lb. - APU0000717311 Eggs, grade A, large, per doz. - APU0000708111 Flour, white, all purpose, per lb. - APU0000701111 Milk, fresh, whole, fortified, per gal. - APU0000709112 Oranges, navel, per lb. - APU0000711311 Rice, white, long grain, uncooked, per lb. - APU0000701312 Tomatoes, field grown, per lb. - APU0000712311 Electricity per KWH - APU000072610 Fuel oil #2 per gallon - APU000072511 Gasoline, all types, per gallon - APU00007471A Gasoline, unleaded regular, per gallon - APU000074714

library(blscrapeR)
library(tidyverse)

df <- bls_api(c("APU0000704111", "APU0000706111","APU0000708111","APU0000709112"), 
              startyear = 2019, endyear = 2020)  %>%
    spread(seriesID, value) %>% dateCast() %>%
   rename(chicken=APU0000706111,egg=APU0000708111,beacon=APU0000704111,milk=APU0000709112)

## REQUEST_SUCCEEDED

ggplot(data = df, aes(x = date)) + 
    geom_line(aes(y = chicken, color = "chicken"),size=.8) +
    geom_line(aes(y = egg, color = "egg"),size=.8) + 
    geom_line(aes(y = beacon, color = "beacon"),size=.8) +
    geom_line(aes(y = milk, color = "milk"),size=.8) +
    labs(title = "Food Prices During COVID19 Pandemic", y="Price", x="Date") +
    theme(legend.position="top", plot.title = element_text(hjust = 0.5))